In battery powered systems it is important to have an accurate estimate of the battery's usable capacity, called State of Charge (SOC). In an analogy to automotive fuel gauges, instrumentation to estimate SOC is called a battery fuel gauge. If a battery fuel gauge overestimates SOC, then the battery might unexpectedly stop functioning, forcing a system being powered by the battery to uncontrollably shut down, which in some cases might result in catastrophic data loss. If a battery fuel gauge underestimates SOC, then a system being powered by the battery might be warned that a battery is discharged when it is actually still has charge available, resulting in an inconvenient and unnecessary shut down or recharging operation. Accordingly, fuel gauge accuracy is important.
Battery fuel gauges range from very simple to very complex. The simplest of gauges involves the method of voltage correlation, in which the SOC is determined using the strong correlation of the battery's open circuit voltage with its state of charge. However, accurate open circuit voltage values can be obtained only when the battery reaches equilibrium upon relaxation after a load, which can be very time consuming. Moreover, the battery will not reach equilibrium if it is always under load, so SOC may not be updated accurately.
Another simple gauging technique, known as Coulomb Counting, uses a current-sense resistor connected in series with the output of the battery. The voltage across the resistor is used to measure current, and the current is integrated during charging and discharging to estimate SOC. However, an external resistor wastes energy and reduces the useable supply voltage.
Another gauging approach is to model the battery as an equivalent circuit. The output voltage of the battery is monitored, current is estimated using the output voltage and the model, and the estimated current is integrated to determine an estimated change of charge. One simple equivalent circuit model (called an R model) assumes the battery is an ideal voltage source with an estimated internal resistance. The current can be estimated based on the open circuit voltage and the voltage drop resulting from current flowing through the estimated internal resistance. However, the R model does not accurately estimate the current because it does not capture the transient voltage behavior that occurs at the onset of a load change.
An improved equivalent circuit model (called an RC model) has at least one parallel resistance/capacitance circuit, with the parallel resistance/capacitance circuit in series with an additional resistance. FIG. 1 illustrates an example of an RC model 100 of a battery. In the example model, there is a voltage source 102 having a voltage VOC, which is the steady state open source voltage of the battery. There is a series resistor RSER. There is also a parallel circuit with a resistor RPAR in parallel with a capacitor CPAR. The model circuit has an output voltage VOUT. A processor (not illustrated) monitors VOUT and estimates the load current iLOAD using the equivalent circuit model 100. The processor integrates the estimated load current iLOAD to obtain an estimated amount of change in charge. An example of how RSER, RPAR, and CPAR are determined may be found in U.S. Patent Application Publication US 2012/0143585, published Jun. 7, 2012, by Barsukov et al., which is incorporated herein for all that it teaches and discloses.
The most sophisticated and most accurate models are physics based, with complex differential equations modeling a large number of electrochemical parameters. Many of the electrochemical parameters are difficult to measure, and the computational complexity may be impractical for portable real-time electronic devices.